Research suggests that assisted reproductive technologies may lead to adverse effects on the offspring. To date, long-term effects from fetal development through adulthood have been scarcely researched. In the present observational study, we aimed to describe growth (body weight, BW; crown-rump length, CRL; and average daily gain, ADG), and growth-related hormone levels (growth hormone, GH; insulin-like growth factor 1, IGF-1; thyroxine, T4; cortisol) of pigs derived from artificial insemination (AI) and from embryos produced in vitro under two different conditions, C-IVP, with Bovine Serum Albumin (BSA), and RF-IVP, with reproductive fluids and BSA, as protein source in culture, from birth to 5 years of age. In vitro-produced animals showed greater BW, CRL and ADG than AI. Additionally, C-IVP animals had greater BW, CRL and ADG than RF-IVP up to 6 months of age. Regarding hormones, GH concentration was greater in RF-IVP compared to AI and C-IVP. In males, IGF-1 levels of RF-IVP were greater than those of AI. Instead, T4 levels of AI males were greater than C-IVP and RF-IVP. Males showed greater IGF-1 and GH than females, the latter only from 1 year old. Instead, females had greater T4 concentration than males. No differences in cortisol were observed between groups or sexes. In conclusion, this study sets reference values of growth and hormone concentrations for adult pigs that are missing in literature. Although the differences observed between the experimental groups were within physiological ranges, there was a greater growth performance in the IVP groups.

OBJECTIVE: To investigate whether improvements in forward bending were related to reductions in pain catastrophizing (PC) and improvements in pain self-efficacy (PSE) in people with chronic low back pain (CLBP) who were undergoing cognitive functional therapy (CFT). DESIGN: Longitudinal observational study. METHODS: Two hundred sixty-one participants with CLBP received CFT. Forward bending was assessed at each treatment session over 13 weeks (average of 4.3 time points per participant [range, 1-8]). Inertial measurement units placed on T12 and S2 measured spinal range of movement (ROM) and velocity. Participants completed the Pain Catastrophizing Scale and the Pain Self-Efficacy Questionnaire online at 0, 3, 6, and 13 weeks. Multivariate, multilevel models evaluated the associations between individual rates of change over time for 3 spinal movement measures (trunk velocity, trunk ROM, and lumbar ROM) as well as PC/PSE. RESULTS: Strong correlations were observed for increased trunk velocity with reduced PC (r = -0.56; 95% confidence interval [CI]: -0.82, -0.01) and increased PSE (r = 0.63; 95% CI: 0.18, 0.87). There was no evidence of an association between changes in trunk ROM and PC (r = -0.06; 95% CI: 0.38, 0.28) or PSE (r = 0.36; 95% CI: -0.27, 0.65) as well as no evidence of an association between lumbar ROM and PC (r = -0.07; 95% CI: -0.63, 0.55) or PSE (r = 0.16; 95% CI: -0.49, 0.69). CONCLUSION: Improvements in PC and PSE were strongly correlated with increased trunk velocity-but not trunk or lumbar ROM-in people with CLBP who were undergoing CFT. These findings are consistent with CFT that explicitly trains "nonprotective" spinal movement in conjunction with positively reframing pain cognitions. J Orthop Sports Phys Ther 2025;55(4):1-11. Epub 12 March 2025. doi:10.2519/jospt.2025.13114.

Testing differences in longitudinal trajectories among distinct groups of population is an important task in many biomedical applications. Motivated by an application in Alzheimer's disease, we develop BayTetra, an innovative Bayesian semiparametric approach for estimating and testing group differences in multivariate longitudinal trajectories. BayTetra jointly models multivariate longitudinal data by directly accounting for correlations among different responses, and uses a semiparametric framework based on B-splines to capture the non-linear trajectories with great flexibility. To avoid overfitting, BayTetra encourages parsimonious trajectory estimation by imposing penalties on the smoothness of the spline functions. The proposed method converts the challenging task of hypothesis testing for longitudinal trajectories into a more manageable equivalent form based on hypothesis testing for spline coefficients. More importantly, by leveraging posterior inference with natural uncertainty quantification, our Bayesian method offers a more robust and straightforward hypothesis testing procedure than frequentist methods. Extensive simulations demonstrate BayTetra's superior performance over alternatives. Applications to the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD) study yield interpretable and valuable clinical insights. A major contribution of this paper is that we have developed an R package BayTetra, which implements the proposed Bayesian semiparametric approach and is the first publicly available software for hypothesis testing on trajectory differences based on a flexible modeling framework.

To evaluate the association between optical coherence tomography (OCT) angiography measurements and progressive retinal nerve fiber layer (RNFL) loss in eyes with mild to moderate open-angle glaucoma.

In this prospective study, 111 quadrants of 59 eyes with mild-moderate open-angle glaucoma were longitudinally evaluated for a minimum of 2 years with at least 3 OCT scans performed. OCT angiography was performed at baseline and vessel densities in the peripapillary and parafoveal regions were determined quadrant-wise. Effect of demographic (age, sex, presence of diabetes and hypertension), clinical (mean and fluctuation of intraocular pressure, presence of pseudoexfoliation, presence of disc hemorrhages, central corneal thickness, baseline mean deviation on visual fields) and OCT angiography parameters (peripapillary and parafoveal vessel densities) on rate of RNFL change was determined using linear mixed models.

Average baseline hemifield mean deviation and quadrant RNFL thickness was -3.5 ±  2.5dB and 97 ± 18µm respectively. The mean follow-up duration was 5.0 ±  1.8 years. The rate of change of quadrant RNFL thickness (RNFL slope) was -1.67 ±  0.2 µm/year. Multivariate mixed models showed that presence of pseudoexfoliation deposits (co-efficient -0.78 ±  0.34, p = 0.025) and optic disc hemorrhages (co-efficient -0.59 ±  0.28, p = 0.040) were associated with a faster rate of RNFL decline. None of the baseline OCT angiography parameters evaluated in this study showed any association with the RNFL slope.

Presence of pseudoexfoliation and optic disc hemorrhages are significant risk factors for glaucoma progression in open-angle glaucoma. Baseline superficial vessel density, as measured on OCT angiography, was not associated with the rate of RNFL loss in mild-moderate open-angle glaucoma.

Cluster or group randomized trials (CRTs) are increasingly used for behavioral as well as system-level interventions in many areas e.g. medicine, psychotherapy, policy, and health service research etc. Sample size determination for each level at the design stage is always a key requirement for any intervention trial including CRT. This work addresses this important issue for a four-level longitudinal CRT via detecting the intervention effect over time. A random intercept and random slope mixed effects linear regression model, including a time-by-intervention interaction is used for modeling. Closed-form expression of the power function and sample size for each level are determined to detect the interaction effect. Other than statistical power consideration, several other factors need attention while designing such CRTs. Optimal allocations accounting for subject attrition and cost constraints have been determined here. How sample size determination based on fixed and random slope models affects when between-subject variations in outcome are anticipated to be significant is also studied. The effect of ignoring cluster levels in a four-level CRT, which is often the case in the absence of an appropriate four-level model, is studied in details. Lastly, the proposed model is illustrated via a real-life human immunodeficiency virus prevention study conducted in the Bahamas.

The linear mixed-effects model (LME) is a conventional parametric method mainly used for analyzing longitudinal and clustered data in genetic studies. Previous studies have shown that this model can be sensitive to parametric assumptions and provides less predictive performance than non-parametric methods such as random effects-expectation maximization (RE-EM) and unbiased RE-EM regression tree algorithms. These longitudinal regression trees utilize classification and regression trees (CART) and conditional inference trees (Ctree) to estimate the fixed-effects components of the mixed-effects model. While CART is a well-known tree algorithm, it suffers from greediness. To mitigate this issue, we used the Evtree algorithm to estimate the fixed-effects part of the LME for handling longitudinal and clustered data in genome association studies.

In this study, we propose a new non-parametric longitudinal-based algorithm called "Ev-RE-EM" for modeling a continuous response variable using the Evtree algorithm to estimate the fixed-effects part of the LME. We compared its predictive performance with other tree algorithms, such as RE-EM and unbiased RE-EM, with and without considering the structure for autocorrelation between errors within subjects to analyze the longitudinal data in the genetic study. The autocorrelation structures include a first-order autoregressive process, a compound symmetric structure with a constant correlation, and a general correlation matrix. The real data was obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling used body mass index (BMI) as the phenotype and included predictor variables such as age, sex, and 25,640 single nucleotide polymorphisms (SNPs).

The results demonstrated that the predictive performance of Ev-RE-EM and unbiased RE-EM was nearly similar. Additionally, the Ev-RE-EM algorithm generated smaller trees than the unbiased RE-EM algorithm, enhancing tree interpretability.

The results showed that the unbiased RE-EM and Ev-RE-EM algorithms outperformed the RE-EM algorithm. Since algorithm performance varies across datasets, researchers should test different algorithms on the dataset of interest and select the best-performing one. Accurately predicting and diagnosing an individual's genetic profile is crucial in medical studies. The model with the highest accuracy should be used to enhance understanding of the genetics of complex traits, improve disease prevention and diagnosis, and aid in treating complex human diseases.

Monitoring calf body weight (BW) before weaning is essential for assessing growth, feed efficiency, health, and weaning readiness. However, labor, time, and facility constraints limit BW collection. Additionally, Holstein calf coat patterns complicate image-based BW estimation, and few studies have explored non-contact measurements taken at early time points for predicting later BW. The objectives of this study were to (1) develop deep learning-based segmentation models for extracting calf body metrics, (2) compare deep learning segmentation with threshold-based methods, and (3) evaluate BW prediction using single-time-point cross-validation with linear regression (LR) and extreme gradient boosting (XGBoost) and multiple-time-point cross-validation with LR, XGBoost, and a linear mixed model (LMM). Depth images from Holstein (n = 63) and Jersey (n = 5) pre-weaning calves were collected, with 20 Holstein calves being weighed manually. Results showed that You Only Look Once version 8 (YOLOv8) deep learning segmentation (intersection over union = 0.98) outperformed threshold-based methods (0.89). In single-time-point cross-validation, XGBoost achieved the best BW prediction (R2 = 0.91, mean absolute percentage error (MAPE) = 4.37%), while LMM provided the most accurate longitudinal BW prediction (R2 = 0.99, MAPE = 2.39%). These findings highlight the potential of deep learning for automated BW prediction, enhancing farm management.

Genotype selection for dry matter yield (DMY) in perennial forage species is based on repeated measurements over time, referred to as longitudinal data. These datasets capture temporal trends and variability, which are critical for identifying genotypes with desirable performance across seasons. In this study, we have presented a random regression model (RRM) approach for selecting genotypes based on longitudinal DMY data generated from 10 breeding trials and three perennial species, alfalfa (Medicago sativa L.), guineagrass (Megathyrsus maximus), and brachiaria (Urochloa spp.). We also proposed the estimation of adaptability based on the area under the curve and stability based on the curve coefficient of variation. Our results showed that RRM always approximated the (co)variance structure into an autoregressive pattern. Furthermore, RRM can offer useful information about longitudinal data in forage breeding trials, where the breeder can select genotypes based on their seasonality by interpreting reaction norms. Therefore, we recommend using RRM for longitudinal traits in breeding trials for perennial species.

The impact of rising ambient temperatures on sleep and its phases under climate change is becoming increasingly concerning but remains underexplored. Sleep, consisting of non-rapid eye movement and rapid eye movement phases, is crucial for health, and insufficient sleep in either phase could have significant implications. Based on sleep monitoring data of 23 million days from 214,445 participants across mainland China, we investigated how daily average temperature affected sleep. For each 10 °C increase in ambient temperature, the odds of sleep insufficiency increased by 20.1%, while total sleep duration decreased by 9.67 minutes, with deep sleep declining the most (by 2.82%). Projections under the unrestricted (SSP5-8.5) greenhouse gas emission scenario suggest that by the end of the century, sleep insufficiency could rise by 10.50%, with an annual loss of 33.28 hours of sleep per person. These findings highlight the potential of climate warming to exacerbate sleep deprivation and degrade sleep quality, especially for the elderly, women, individuals with obesity, and regions of South, Centre and East.

Motivated by the Swedish Betula study, we consider the joint modeling of longitudinal memory assessments and the hazard of dementia. In the Betula data, the time-to-dementia onset or its absence is available for all participants, while some memory measurements are missing. In longitudinal studies of aging, one cannot rule out the possibility of dropout due to health issues resulting in missing not at random longitudinal measurements. We, therefore, propose a pattern-mixture sensitivity analysis for missing not-at-random data in the joint modeling framework. The sensitivity analysis is implemented via multiple imputation as follows: (i) multiply impute missing not at random longitudinal measurements under a set of plausible pattern-mixture imputation models that allow for acceleration of memory decline after dropout, (ii) fit the joint model to each imputed longitudinal memory and time-to-dementia dataset, and (iii) combine the results of step (ii). Our work illustrates that sensitivity analyses via multiple imputations are an accessible, pragmatic method to evaluate the consequences of missing not at-random data on inference and prediction. This flexible approach can accommodate a range of models for the longitudinal and event-time processes. In particular, the pattern-mixture modeling approach provides an accessible way to frame plausible missing not at random assumptions for different missing data patterns. Applying our approach to the Betula study shows that worse memory levels and steeper memory decline were associated with a higher risk of dementia for all considered scenarios.

Regulating gestational weight gain (GWG) in pregnant women with overweight or obesity is difficult, particularly because of the narrow range of recommended GWG for optimal health outcomes. Given that many pregnant women show excessive GWG and considering the lack of a "gold standard" intervention to manage GWG, there is a timely need for effective and efficient approaches to regulate GWG. We have enhanced the Healthy Mom Zone (HMZ) 2.0 intervention with a novel digital platform, automated dosage changes, and personalized strategies to regulate GWG, and our pilot study demonstrated successful recruitment, compliance, and utility of our new control system and digital platform.

The goal of this paper is to describe the study protocol for a randomized controlled optimization trial to examine the efficacy of the enhanced HMZ 2.0 intervention with the new automated control system and digital platform to regulate GWG and influence secondary maternal and infant outcomes while collecting implementation data to inform future scalability.

This is an efficacy study using a randomized controlled trial design. HMZ 2.0 is a multidosage, theoretically based, and individually tailored adaptive intervention that is delivered through a novel digital platform with an automated link of participant data to a new model-based predictive control algorithm to predict GWG. Our new control system computes individual dosage changes and produces personalized physical activity (PA) and energy intake (EI) strategies to deliver just-in-time dosage change recommendations to regulate GWG. Participants are 144 pregnant women with overweight or obesity randomized to an intervention (n=72) or attention control (n=72) group, stratified by prepregnancy BMI (<29.9 vs ≥30 kg/m2), and they will participate from approximately 8 to 36 weeks of gestation. The sample size is based on GWG (primary outcome) and informed by our feasibility trial showing a 21% reduction in GWG in the intervention group compared to the control group, with 3% dropout. Secondary outcomes include PA, EI, sedentary and sleep behaviors, social cognitive determinants, adverse pregnancy and delivery outcomes, infant birth weight, and implementation outcomes. Analyses will include descriptive statistics, time series and fixed effects meta-analytic approaches, and mixed effects models.

Recruitment started in April 2024, and enrollment will continue through May 2027. The primary (GWG) and secondary (eg, maternal and infant health) outcome results will be analyzed, posted on ClinicalTrials.gov, and published after January 2028.

Examining the efficacy of the novel HMZ 2.0 intervention in terms of GWG and secondary outcomes expands the boundaries of current GWG interventions and has high clinical and public health impact. There is excellent potential to further refine HMZ 2.0 to scale-up use of the novel digital platform by clinicians as an adjunct treatment in prenatal care to regulate GWG in all pregnant women.

DERR1-10.2196/66637.

Autism spectrum disorder (ASD) is associated with mitochondrial dysfunction, but studies demonstrating the efficacy of treatments are scarce. We sought to determine whether a mitochondrial-targeted dietary supplement designed for children with ASD improved mitochondrial function and ASD symptomatology using a double-blind placebo-controlled cross-over design. Sixteen children [mean age 9 years 4 months; 88% male] with non-syndromic ASD and mitochondrial enzyme abnormalities, as measured by MitoSwab (Religen, Plymouth Meeting, PA, USA), received weight-adjusted SpectrumNeeds® (NeuroNeeds, Old Lyme, CT, USA) and QNeeds® (NeuroNeeds, Old Lyme, CT, USA) and placebos matched on taste, texture and appearance during two separate 12-week blocks. Which product was received first was randomized. The treatment significantly normalized citrate synthase and complex IV activity as measured by the MitoSwab. Mitochondrial respiration of peripheral blood mononuclear cell respiration, as measured by the Seahorse XFe96 (Agilent, Santa Clara, CA, USA) with the mitochondrial oxidative stress test, became more resilient to oxidative stress after the treatment, particularly in children with poor neurodevelopment. The mitochondrial supplement demonstrated significant improvement in standardized parent-rated scales in neurodevelopment, social withdrawal, and hyperactivity with large effect sizes (Cohen's d' = 0.77-1.25), while changes measured by the clinical and psychometric instruments were not significantly different. Adverse effects were minimal. This small study on children with ASD and mitochondrial abnormalities demonstrates that a simple, well-tolerated mitochondrial-targeted dietary supplement can improve mitochondrial physiology and ASD symptoms. Further larger controlled studies need to verify and extend these findings. These findings are significant as children with ASD have few other effective treatments.

We evaluated 128 GBA and 432 nonGBA Parkinson's disease (PD) subjects available from Parkinson's Progression Markers Initiative. Baseline clinical features and dopaminergic activity were assessed, together with clinical follow-up (6.87 ± 3.2 years). Survival analyses assessed the independent and interactive effects of sex and GBA1 mutations on cognitive decline. At baseline, GBA-PD males showed severe motor impairment, sleep disorders and memory deficits. Despite milder motor deficit, compared to GBA-PD males, GBA-PD females showed greater dopaminergic denervation, suggesting the effect of neural reserve. In longitudinal assessment, GBA-PD males showed greater MoCA rate of change per year and greater risk of cognitive impairment than GBA-PD females and nonGBA-PD. In GBA-PD males, both late age at onset and "severe/mild" GBA variants were associated with increased risk of cognitive impairment. Male sex and GBA1 carrier status have an additive value in increasing the risk of cognitive decline in PD. The effect of sex on GBA1-related pathology warrants further examination to address future trials design and patients' selection.

Chronic skin conditions can have psychosocial and somatic implications, influencing well-being and quality of life. This systematic review and meta-analysis aimed to synthesise evidence on the prevalence of comorbid mental health difficulties in 0-25-year-olds with chronic skin conditions. A secondary aim included identifying factors associated with resilience. The narrative synthesis included 45 studies. Four meta-analyses were performed with moderate-high quality studies, one for each outcome: diagnosed mental disorders; mental health symptoms; suicidal behaviour; socio-emotional and behavioural difficulties. The pooled prevalence of diagnosed mental disorders was 1.2% (95% CI = 0.2-6.1); of mental health symptoms was 22.6% (95% CI = 18.9-26.7); of suicidal behaviour was 7.8% (95% CI = 1.4-3.1); of socio-emotional and behavioural difficulties was 20.9% (95% CI = 14.7-28.8). Findings demonstrate the pooled prevalence of comorbid mental health difficulties in youth with chronic skin conditions.

Younger patient age (coefficient: 0.10, P =0.04) and greater peak IOP during follow-up (coefficient: -0.14, P =0.03), but not baseline optical microangiography parameters, were significantly associated with a faster rate of RNFL loss in mild-moderate PACG.

To evaluate the association between optical microangiography (OMAG) measurements and progressive retinal nerve fiber layer (RNFL) loss in primary angle closure glaucoma (PACG).

In a prospective study, 45 eyes of 30 PACG patients (86 hemifields) with mild to moderate functional damage were longitudinally studied for at least 2 years and with a minimum of 3 optical coherence tomography (OCT) examinations. OMAG imaging was performed at the baseline visit. Effect of clinical parameters (age, sex, presence of systemic diseases, central corneal thickness, mean, peak, and fluctuation of intraocular pressure during follow-up), baseline hemifield mean deviation (MD) and baseline OMAG [quadrant peripapillary and macular perfusion density(PD)] on the rate of RNFL change was evaluated using linear mixed models.

The average (±SD) hemifield MD, RNFL thickness, peripapillary PD and macular PD of the analyzed quadrants at baseline were -6.0±3.4 dB, 89±21 µm, 40.1±3.5%, and 29.6±10.3%, respectively. The rate of quadrant RNFL change was -2.5±1.7 µm/year. Multivariate mixed models showed that younger patient age (coefficient: 0.10, P =0.04) and higher peak IOP during follow-up (coefficient: -0.14, P =0.03) were significantly associated with a faster rate of RNFL loss.

Younger patient age and greater peak IOP during follow-up were significantly associated with a faster rate of RNFL loss in PACG patients with mild to moderate severity of functional damage. None of the OMAG parameters at baseline were associated with RNFL thinning suggesting a limited role of OCTA imaging in predicting structural progression in mild-moderate PACG.

The article proposes a robust approach to jointly modeling multiple repeated clinical measures with intricate features. More specifically, we aim to expand the scope of the multivariate linear mixed model by using the multivariate contaminated normal distribution. The proposed model, called the multivariate contaminated normal linear mixed model with censored and missing responses (MCNLMM-CM), is designed to handle minor outliers effectively, while simultaneously accommodating censored measurements and intermittent missing responses. An expectation conditional maximization either algorithm is developed to estimate the parameters of the proposed model in situations involving missing at random responses. We also provide techniques for approximating the asymptotic standard errors of the parameters, recovering censored data, imputing missing values, and identifying outliers. A simulation study is conducted to evaluate the finite-sample properties of the parameter estimators and demonstrate the superior performance of the proposed model compared to existing models. The proposed methodology is inspired by and applied to data from the Alzheimer's disease neuroimaging initiative cohort study, which involves longitudinal clinical measurements of patients with mild cognitive impairment.

Curve matching can predict the height trajectories of children by analyzing longitudinal growth data. We extended the method to improve the prediction of response to long-acting growth hormone treatment in children with growth hormone deficiency (GHD).

We analyzed data from a previous real-world study with a 36-month treatment of PEGylated recombinant human growth hormone (PEG-rhGH). The matching database comprises height measures imputed using the broken stick method. For curve matching, we proposed a flexible hyperparameter selection approach to determining the number of similar patients.

The matching database included 681 patients, with an average of 12.20 ± 2.09 height measurements per patient. Our approach demonstrated significantly improved prediction accuracy compared with the previous approach using a fixed number of similar patients (mean squared errors of 0.0412 ± 0.1156 vs. 0.564 ± 0.1639, 0.851 ± 0.2627, and 0.1077 ± 0.2960 for 5, 10, and 15 similar patients, respectively, all P < 0.05). The optimal prediction scenario was having four height measurements within the first six months and predicting height trajectories from there on.

By extending curve matching with flexible hyperparameter selection, we accurately predicted the response to long-acting PEG-rhGH in the GHD children included in this study.

This study included 102 open-angle glaucoma (OAG) eyes with or without a localized choroidal microvasculature dropout (CMvD) at the inferior hemiretina, matched for age (≤ 10 years), axial length (≤ 1 mm), and visual field severity (≤ 1dB), and with a minimum 2-year follow-up. Serial thickness [circumpapillary retinal nerve fiber layer (cpRNFLT) and macular ganglion cell-inner plexiform layer thickness (mGCIPLT)], and vessel density (VD) [circumpapillary (cpVD) and macular VD (mVD)] parameters were obtained. The rate of change in each parameter at both the superior (CMvD-unaffected) and inferior (CMvD-affected) hemiretina were compared between matched eyes with (CMvD+) and without CMvD (CMvD-). Clinical factors associated with the rate of change in each parameter both globally and at the CMvD-unaffected hemiretina were also evaluated. CMvD + eyes showed significantly faster rates of VD and thickness loss at both the CMvD-affected and -unaffected hemiretina. In addition, CMvD was significantly associated with rapid loss of both VD and thickness parameters globally and at the CMvD-unaffected superior hemiretina. In conclusion, OAG eyes with CMvD show significantly faster rates of VD and thickness loss at both the CMvD-affected and unaffected hemiretina. A localized CMvD is an independent predictor of globally rapid structural loss in OAG eyes.

Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPAGRM, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPAGRM can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid strategy incorporating saddlepoint approximation greatly increases the accuracy to analyze low-frequency and rare genetic variants, especially in unbalanced phenotypic distributions. We also introduce SPAGRM(CCT) to aggregate the results following different models via Cauchy combination test. Extensive simulations and real data analyses demonstrated that SPAGRM maintains well-controlled type I error rates and SPAGRM(CCT) can serve as a broadly effective method. Applying SPAGRM to 79 longitudinal traits extracted from UK Biobank primary care data, we identified 7,463 genetic loci, making a pioneering attempt to conduct GWAS for these traits as longitudinal traits.

Gait Speed Reserve (GSR) expresses a difference between fast and comfortable gait speed and may have an impact on everyday functioning. It was also hypothesized as a useful proxy measure of physiological reserve. However, height-normalizing values of GSR and its associated factors have not been evaluated in a general population of older adults. Therefore, we aimed to investigate the distribution of height-normalized GSR (HN-GSR) in an elderly population-based cohort from urban and rural areas (n = 4342) aged 60-93 years and evaluate associated physiological and lifestyle factors. Using linear mixed models, we identified gender and nine modifiable factors as significantly associated with HN-GSR across four age groups. Better handgrip strength, cognition and standing balance, higher physical activity level, larger calf circumference, and less smoking had positive associations with HN-GSR, while female gender, more leg pain, higher weight and, alcohol consumption had opposite effects. The Marginal R2 imply that this model explained 26% of the variance in HN-GSR. Physical activity and handgrip strength varied across age groups in impact on HN-GSR. The differences were however comparatively minor. In this large cohort study of older adults, we proposed for the first time that factors associated with HN-GSR represented multi-domain features that are in line with previous findings reported for GSR. Measuring HN-GSR/GSR may help clinicians identify early physiological impairments or unhealthy lifestyle habits, especially among older women, and may also have safety implications in daily life. Further work is needed to find out if measuring HN-GSR/GSR may be useful in identifying adverse health outcomes and overall physiological reserve.

The hostile immune environment created by allotransplantation can accelerate pathologic tissue remodeling. Both overt and indolent inflammatory insults propel this remodeling, but there is a paucity of tools for monitoring the speed and severity of remodeling over time.

This retrospective cohort consisted of n = 2,167 digitized heart transplant biopsy slides along with records of prior inflammatory events and future allograft outcomes (cardiac death or allograft vasculopathy). Utilizing computational pathology analysis, biopsy images were analyzed to identify the pathologic stromal changes associated with future allograft loss or vasculopathy. Biopsy images were then analyzed to assess which historical inflammatory events drive progression of these pathologic stromal changes.

The top 5 features of pathologic stromal remodeling most associated with adverse allograft outcomes were also strongly associated with histories of both overt and indolent inflammatory events. Compared to controls, a history of high-grade or treated rejection was significantly associated with progressive pathologic remodeling and future adverse outcomes (32.9% vs 5.1%, p < 0.001). A history of recurrent low-grade rejection and Quilty lesions was also significantly associated with pathologic remodeling and adverse outcomes vs controls (12.7% vs 5.1%, p = 0.047). A history of high-grade or treated rejection in the absence of recurrent low-grade rejection history was not associated with pathologic remodeling or adverse outcomes (7.1% vs 5.1%, p = 0.67).

A history of both traditionally treated and traditionally ignored alloimmune responses can predispose patients to pathologic allograft remodeling and adverse outcomes. Computational pathology analysis of allograft stroma yields translationally relevant biomarkers, identifying accelerated remodeling before adverse outcomes occur.

The data that support the findings of this study are presented in the manuscript and extended data sections. Unprocessed raw data are available from the corresponding author upon reasonable request. Source code for the stromal feature analysis pipeline is hosted on GitHub and freely available: https://github.service.emory.edu/CYUAN31/Pathomics_StromalBioMarker_in_Myocardium.git.

Interindividual variations in efavirenz (EFV) plasma concentrations are extensive, but paediatric data on its consequences for viral control are scarce. The aim of this study was to explore the role of genetic variation in achieving therapeutic efavirenz plasma concentrations in a cohort of Ugandan children and the linkage between genetic CYP2B6 variants, EFV plasma variability, viral resistance and viral outcome.

Ninety-nine treatment-naïve children, aged 3-12 years and living with HIV, were followed for 24 weeks after ART initiation assessing mid-dose efavirenz plasma concentrations, HIV RNA, HIV drug resistance and adherence. Polymorphisms in genes coding for drug-metabolizing enzymes were genotyped. Efavirenz concentrations were determined by liquid chromatography coupled with high-resolution tandem mass spectrometry. Metabolizer phenotype was predicted from composite genotypes of CYP2B6 (c.516G>T and c.983 T>C). A mixed effects restricted maximum likelihood regression model was used to identify important factors for efavirenz exposure.

Efavirenz plasma concentrations were below the therapeutic interval (1000-4000 mg/mL) in 12-17% and above in 21-24% of measurements. Eight children had persisting subtherapeutic concentrations, five of which failed virologically and three acquired at least one new resistant mutation. Multivariate modelling explained 70% of interindividual variation in plasma concentration, with treatment duration, adherence, CYP2B6c.136A>G, and metabolizer phenotype as independent predictors of EFV concentration. In univariate analysis, metabolizer phenotype explained 50% of interindividual variation.

Metabolizer phenotype explained 50% of interindividual variation in efavirenz plasma concentration. Autoinduction was not confirmed and >33% of the concentrations were outside the therapeutic interval. Subtherapeutic concentrations worsened virological resistance and outcomes. Genotype-based dosing may help avert both sub- and supratherapeutic efavirenz plasma concentrations in Ugandan children.

Earthquake insurance is a critical risk management strategy that contributes to improving recovery and thus greater resilience of individuals. Insurance companies construct premiums without taking into account spatial correlations between insured assets. This leads to potentially underestimating the risk, and therefore the exceedance probability curve. We here propose a mixed-effects model to estimate losses per ward that is able to account for heteroskedasticity and spatial correlation between insured losses. Given the significant impact of earthquakes in New Zealand due to its particular geographical and demographic characteristics, the government has established a public insurance company that collects information about the insured buildings and any claims lodged. We thus develop a two-level variance component model that is based on earthquake losses observed in New Zealand between 2000 and 2021. The proposed model aims at capturing the variability at both the ward and territorial authority levels and includes independent variables, such as seismic hazard indicators, the number of usual residents, and the average dwelling value in the ward. Our model is able to detect spatial correlation in the losses at the ward level thus increasing its predictive power and making it possible to assess the effect of spatially correlated claims that may be considerable on the tail of loss distribution.

Patterns of calcium dysregulation resulting in low total serum calcium concentrations (tCa) at 4 DIM, known as dyscalcemia, commonly occur in multiparous Holsteins. Dyscalcemia is associated with risk of disease, decreased production, and poor reproductive performance. Inflammation is well-documented early in lactation and is associated with similarly suboptimal outcomes. The acute phase response produces markers and mediators of inflammation; therefore, the objective of our case-control study was to evaluate postpartum patterns of 3 positive acute phase proteins in cows with and without dyscalcemia. We hypothesized that dyscalcemic cows would experience more activated inflammation than eucalcemic cows and that inflammation would precede dyscalcemia diagnosis. Multiparous Holstein cows at 2 commercial dairy farms in central New York were enrolled from a parent study based on tCa at 4 DIM, at a 2:1 ratio of eucalcemic (tCa >2.3 mmol/L; n = 32) to dyscalcemic cows (tCa <2.2 mmol/L; n = 16). Blood was collected 1 to 3 d before parturition and once every 24 h postpartum through 4 DIM. Samples were analyzed for 3 acute phase proteins, serum amyloid A (SAA), haptoglobin and LPS binding protein (LBP). Patterns of protein concentrations in blood over time were compared using linear mixed effects models including fixed effects of calcium status group, time, parity group, farm, relevant 2-way interactions, and the random effect of cow. Overall, dynamics of acute phase proteins showed that dyscalcemic cows experienced increased acute phase responses compared with eucalcemic cows, and that these responses preceded dyscalcemia diagnosis at 4 DIM. Dyscalcemic cows had elevated concentrations of SAA beginning at 2 DIM (eucalcemic: mean = 13.88 µg/mL, 95% CI = 11.34 to 16.99 µg/mL; dyscalcemic: mean = 32.95 µg/mL, 95% CI = 24.55 to 44.21 µg/mL) and continuing through 4 DIM (eucalcemic: mean = 8.14 µg/mL, 95% CI = 6.66 to 9.95 µg/mL; dyscalcemic: mean = 30.01 µg/mL, 95% CI = 22.60 to 39.83 µg/mL). Haptoglobin concentrations were also elevated in the blood of dyscalcemic cows from 2 DIM (eucalcemic: mean = 0.39 g/L, 95% CI = 0.31 to 0.49 g/L; dyscalcemic: mean = 1.11 g/L, 95% CI = 0.79 to 1.56 g/L) through 4 DIM (eucalcemic: mean = 0.27 g/L, 95% CI = 0.21 to 0.34 g/L; dyscalcemic: mean = 1.65 g/L, 95% CI = 1.19 to 2.28 g/L). Concentrations of LBP exhibited a different pattern with a small difference between groups at 3 DIM (eucalcemic: mean = 4.67 µg/mL, 95% CI = 4.02 to 5.42 µg/mL; dyscalcemic: mean = 7.91 µg/mL, 95% CI = 6.49 to 9.63 µg/mL) that became larger at 4 DIM (eucalcemic: mean = 4.88 µg/mL, 95% CI = 4.22 to 5.64 µg/mL; dyscalcemic: mean = 10.79 µg/mL, 95% CI = 8.84 to 13.17 µg/mL). Our work supports the hypothesis that dyscalcemia and inflammatory activity are associated in dairy cows under naturally occurring postpartum conditions. Although the causal structure of this relationship remains unknown, improved understanding of inflammation and dyscalcemia may provide insight into mechanisms by which some cows experience maladaptation during the early postpartum period.

To investigate the incidence and predictors of visual acuity loss after surgery for epiretinal membrane in glaucomatous eyes.

A prospective cohort study examining visual acuity and central visual fields (VFs, Humphrey 10-2) at baseline and 3, 6, and 12 months after vitrectomy with internal limiting membrane peeling for epiretinal membrane in the glaucoma (47 eyes of 43 patients) and control (46 eyes of 46 patients) groups. Visual acuity and VF tests were repeated for ≥1.5 years only for the glaucoma group. Factors associated with substantial visual acuity loss (>0.2 logarithm of the minimal angle of resolution [approximately >2 lines on the Snellen chart] from baseline) were determined using a Cox proportional hazards model.

Until 1 year postoperatively, no substantial visual acuity loss occurred and postoperative visual acuity improved significantly and similarly in both groups ( P < 0.001 vs. baseline, P > 0.15 between 2 groups). Substantial visual acuity loss occurred in 8 eyes (17%) with glaucoma ≥1.5 years postoperatively, which was associated with worse preoperative VF mean deviation and 1-year mean decrease in postoperative VF mean deviation (hazard ratio = 0.83-0.72; P = 0.018, <0.001, respectively).

Substantial visual acuity loss occurred long after epiretinal membrane surgery in eyes with glaucoma, which was associated with worse preoperative central VFs and greater central VF deterioration during the first postoperative year.

The Cognitive Bias (CogBIAS) hypothesis proposes that cognitive biases develop as a function of environmental influences (which determine the valence of biases) and the genetic susceptibility to those influences (which determines the potency of biases). The current study employed a longitudinal, polygenic-by-environment approach to examine the CogBIAS hypothesis. To this end, measures of life experiences and polygenic scores for depression were used to assess the development of memory and interpretation biases in a three-wave sample of adolescents (12-16 years) (N = 337). Using mixed effects modeling, three patterns were revealed. First, positive life experiences (PLEs) were found to diminish negative and enhance positive forms of memory and social interpretation biases. Second, and against expectation, negative life experiences and depression polygenic scores were not associated with any cognitive outcomes, upon adjusting for psychopathology. Finally, and most importantly, the interaction between high polygenic risk and greater PLEs was associated with a stronger positive interpretation bias for social situations. These results provide the first line of polygenic evidence in support of the CogBIAS hypothesis, but also extend this hypothesis by highlighting positive genetic and nuanced environmental influences on the development of cognitive biases across adolescence.

Intelligence is known to predict survival, but it remains unclear whether cognitive abilities differ in their relationship to survival in old age. We analyzed longitudinal data of 516 healthy adults (age: M = 84.92 years, SD = 8.66 years at Wave 1) from the Berlin Aging Study (Germany) on nine tasks of perceptual speed, episodic memory, verbal fluency, and verbal knowledge, and a general composite intelligence score. There were eight waves, with up to 18 years of follow-up; all participants were deceased by the time of analysis. We used a joint multivariate longitudinal survival model to estimate the unique contribution of each cognitive ability in terms of true (i.e., error-free) current value and current rate of change when predicting survival. Additional survival covariates included age at first occasion, sex, sociobiographical status, and suspected dementia. Only the two verbal-fluency measures were uniquely predictive of mortality risk. Thus, verbal fluency showed more salient associations with mortality risk than did measures of perceptual speed, episodic memory, and verbal knowledge.

Chronic pain is common among individuals with dialysis-dependent kidney failure.

To evaluate the effectiveness of pain coping skills training (PCST), a cognitive behavioral intervention, on pain interference.

This multicenter randomized clinical trial of PCST vs usual care was conducted across 16 academic centers and 103 outpatient dialysis facilities in the US. Adults undergoing maintenance hemodialysis and experiencing chronic pain were randomly assigned to PCST or usual care in a 1:1 ratio. Participants were followed in the trial for 36 weeks. Enrollment began on January 4, 2021, and follow-up ended on December 21, 2023.

PCST consisting of 12 weekly coach-led sessions via video or telephone conferencing, followed by 12 weeks of daily interactive voice response sessions. Usual care had no trial-driven pain intervention.

The primary outcome was pain interference measured with the Brief Pain Inventory (BPI) Interference subscale (score range of 0-10, with higher scores indicating more pain interference). Secondary outcomes included pain intensity, pain catastrophizing, quality of life, depression, and anxiety.

A total of 643 participants (mean [SD] age, 60.3 [12.6] years; 288 [44.8%] female) were randomized, with 319 assigned to PCST and 324 assigned to usual care. At week 12 (primary end point), the PCST group had a larger reduction in the BPI Interference score than the usual care group (between-group difference, -0.49; 95% CI, -0.85 to -0.12; P = .009). The effect persisted at week 24 (between-group difference in BPI Interference score, -0.48; 95% CI, -0.86 to -0.11) but was diminished at week 36 (between-group difference in BPI Interference score, -0.34; 95% CI, -0.72 to 0.04). A decrease in BPI Interference score greater than 1 point (minimal clinically important difference) occurred in 143 of 281 participants (50.9%) in the PCST group vs 108 of 295 participants (36.6%) in the usual care group at 12 weeks (odds ratio, 1.79; 95% CI, 1.28-2.49) and 142 of 258 participants (55.0%) in the PCST group vs 113 of 264 participants (42.8%) in the usual care group at 24 weeks (odds ratio, 1.59; 95% CI, 1.13-2.24). Favorable changes with PCST were also apparent for secondary outcomes of pain intensity, quality of life, depression, and anxiety at weeks 12 and/or 24, as well as for pain catastrophizing at weeks 24 and 36.

In this randomized clinical trial of patients undergoing maintenance hemodialysis, PCST had benefits on pain interference and other pain-associated outcomes. While the effect on the overall cohort was of modest magnitude, the intervention resulted in a clinically meaningful improvement in pain interference for a substantial proportion of participants.

ClinicalTrials.gov Identifier: NCT04571619.

Sickle cell disease (SCD) is a single-gene illness characterized by chronic inflammation, decreased quality of life, and early mortality; however, outcomes are highly variable between individuals, suggesting a substantial role of social and environmental factors in disease outcomes. Data suggest that individuals living with SCD have greater eosinophil counts and activation, and higher prevalence of asthma and wheezing than those without SCD, suggesting a role for eosinophilic inflammation in SCD. In other diseases, eosinophilic inflammation has been linked to social and environmental factors, particularly in minoritized populations. To date, however, few human studies have explored the pathophysiology of social and environmental exposures in SCD. This study tested whether eosinophilic inflammation was related to location-based measures of social disadvantage or public housing in 79 individuals with SCD, without diagnoses of asthma, who were prospectively followed over one year. Home addresses were geocoded and matched to principal-components derived, validated measures of local neighborhood social disadvantage and to locations of public housing facilities. Serum peripheral eosinophils, IL-13 and IL-5 were measured every 8 weeks. In fully-adjusted models, statistically significant, linear relationships were observed between the degree of social disadvantage and level of eosinophilic inflammation; however, the direction of that relationship was opposite for patients who live in public housing and those who do not. For those living in public housing, greater social disadvantage was associated with increased eosinophilic inflammation. For those in private housing, greater social disadvantage was associated with progressively less eosinophilic inflammation. These strong, and somewhat unexpected, relationships demonstrate that subtle differences in social exposures and home environment have differential effects on inflammatory profiles which may have larger implications for disease and health, especially in chronic diseases such as SCD. To understand the mechanisms of these effects may require highly granular studies that catalog the many factors underlying the social environment and inflammation.

The genetic basis of complex traits involves the function of many genes with small effects as well as complex gene-gene and gene-environment interactions. As one of the major players in complex diseases, the role of gene-environment interactions has been increasingly recognized. Motivated by epidemiology studies to evaluate the joint effect of environmental mixtures, we developed a functional varying-index coefficient model (FVICM) to assess the combined effect of environmental mixtures and their interactions with genes, under a longitudinal design with quantitative traits. Built upon the previous work, we extend the FVICM model to accommodate binary longitudinal traits through the development of a generalized functional varying-index coefficient model (gFVICM). This model examines how the genetic effects on a disease trait are nonlinearly influenced by a combination of environmental factors. We derive an estimation procedure for the varying-index coefficient functions using quadratic inference functions combined with penalized splines. A hypothesis testing procedure is proposed to evaluate the significance of the nonparametric index functions. Extensive Monte Carlo simulations are conducted to evaluate the performance of the method under finite samples. The utility of the method is further demonstrated through a case study with a pain sensitivity dataset. SNPs were found to have their effects on blood pressure nonlinearly influenced by a combination of environmental factors.

Premenstrual dysphoric disorder (PMDD) is a cyclic mood disorder affecting around 2%-5% of women of reproductive age. Pharmacological interventions exist, but many patients with PMDD experience residual symptoms, discontinue medications or refrain from them due to side effects. Thus, non-pharmacological treatments are needed as an alternative or additive treatment strategy. Evidence indicates that cognitive behavioural therapy (CBT) is a promising candidate. However, further research is required to establish its efficacy and identify ways to improve the treatment. Specifically, incorporating components targeting emotional and interpersonal dysregulation could theoretically enhance its effects. Furthermore, increasing the generally low accessibility of CBT for PMDD necessitates scalable and cost-effective ways to deliver treatment. The current study aims to evaluate the effects and cost-effectiveness of an internet-delivered CBT (ICBT) intervention for PMDD incorporating skills training in emotion regulation and interpersonal effectiveness.

The study is a parallel two-group randomised controlled trial with 1:1 allocation to 8 weeks of therapist-guided ICBT or a waitlist control condition. Following recruitment and inclusion, 164 individuals aged 18-45 years who fulfil the Diagnostic Manual of Mental Disorders-5 criteria for PMDD will be randomly assigned to the two groups. Primary outcomes are pretreatment to post-treatment group differences in premenstrual symptoms and their impact on everyday life, as well as psychological and functional impairment during the premenstrual phase. Secondary outcomes include treatment effects on quality of life and difficulties in emotion regulation. Long-term treatment effects will be assessed 6 and 12 months postintervention. Data will be analysed using latent Gaussian process modelling and linear mixed models. The economic evaluation will analyse individual-level societal costs and outcomes between trial arms. Recruitment is expected to begin in February 2025, with study completion anticipated by February 2028.

The study has been approved by the Swedish Ethical Review Authority (2023-00655-01). Results will be disseminated via presentations and publications in international journals and national outlets for clinicians and patients with PMDD.

PS2024_v1.

NCT06496139.

Breast cancer survivors undergoing long-term endocrine therapy often experience multiple symptoms, including pain, fatigue, sleep disturbance, hot flashes, anxiety, and depression. This study explored the feasibility and acceptability of integrating acupuncture for symptom management in medically underserved breast cancer survivors.

This randomized controlled trial was conducted at two clinics serving medically underserved populations. Breast cancer survivors (N = 62) were randomized to receive acupuncture (n = 31) or usual care (n = 31). The acupuncture group underwent 10 sessions over 5 weeks. Symptoms were assessed at baseline and Weeks 6 and 12.

The majority of participants (55%) were Black, mean age was 55.2 ± 9.3 years, and 62.9% had a household income below $55,000. Retention (90.3%), engagement (93.1%), and acceptability (92.8%) rates were high, demonstrating that integrating acupuncture into care for medically underserved breast cancer survivors is both feasible and acceptable. At Week 6, the acupuncture group showed significant reduction compared to the usual care group in pain, fatigue, sleep disturbance, depression, anxiety, and the symptom cluster score. All improvements persisted to Week 12 except for those in anxiety.

Integrating acupuncture for symptom management in medically underserved breast cancer survivors is both feasible and acceptable. This approach offers potential benefits for reducing multiple symptoms and addressing health disparities.

In African Regional Economic Communities (RECs), notable and enduring disparities exist in health outcomes. This study investigates the impact of macro-level characteristics of countries on health outcomes disparities within the African Regional Economic groupings. The study used panel data from the World Bank Development Indicators (WDI) and the Worldwide Governance Indicators (WGI), spanning 37 African countries, grouped into eight RECs between 2000 and 2019. We employed infant and under-five mortality rates and life expectancy at birth as indicators of health outcomes.

The study used a multilevel linear (ML) mixed-effect approach to examine the influence of country-level factors on health outcome disparities within the eight African RECs recognized by the African Union.

The findings show that higher unemployment rates and HIV incidence exacerbate these disparities, while a growing elderly population and improved access to basic drinking water can mitigate them. Increased internet usage correlates with higher within-regional inequalities in child mortality rates but reduces disparities in life expectant at birth. Urbanization trends contribute to lower-intra-regional inequality in infant mortality rates and life expectancy at birth. Higher domestic government health expenditure as a share of general government spending is linked to reduced disparities in under-five and infant mortality rates. Still, it increases inequalities in life expectancy at birth within the regional groupings. Moreover, a higher proportion of the population below 15 years old and trade gains positively influence regional disparities in life expectancy. Conversely, DTP immunization coverage among children aged 12-23 months is associated with higher within-regional inequality in infant mortality rates.

Polices aimed at reducing unemployment rates and HIV incidence should be prioritized. In addition, governments should invest in elderly care programs and infrastructure development for water supply. Efforts to promote internet access should be complemented by interventions to enhance child health and healthcare accessibility. Encouraging urban planning policies that prioritize developing healthcare infrastructure and facilitating healthcare access in urban areas is crucial. Furthermore, Governments should increase their health expenditure allocation in general government spending. Promoting strategies to enhance healthcare access and quality for specific demographics, alongside leveraging trade gains to invest in healthcare infrastructure and services, is imperative. Targeted interventions ensuring equitable access to immunization services should also be emphasized.

Heart failure (HF) is one of the most common causes of hospital readmission in the United States. These hospitalizations are often driven by insufficient self-care. Commercial mobile health (mHealth) technologies, such as consumer-grade apps and wearable devices, offer opportunities for improving HF self-care, but their efficacy remains largely underexplored.

The objective of this study was to examine the feasibility, acceptability, safety, and preliminary efficacy of a patient-centered mHealth intervention (iCardia4HF) that integrates 3 consumer mHealth apps and devices (Heart Failure Health Storylines, Fitbit, and Withings) with a program of individually tailored SMS text messages to improve HF self-care.

We conducted a phase 1 randomized controlled trial. Eligible patients had stage C HF, were aged ≥40 years, and had New York Heart Association (NYHA) class I, II, or III HF. Patients were randomly assigned to either iCardia4HF plus usual care or to usual care only and were observed for 8 weeks. Key feasibility measures were recruitment and retention rates. The primary efficacy outcome was change in HF self-care subscale scores (maintenance, symptom perception, and self-care management) at 8 weeks, assessed with the Self-Care Heart Failure Index (SCHFI; version 7.2). Key secondary outcomes were modifiable behaviors targeted by the intervention (health beliefs, self-efficacy, and HF knowledge), health status, and adherence to daily self-monitoring of 2 core vital signs (body weight and blood pressure).

A total of 27 patients were enrolled in the study and randomly assigned to iCardia4HF (n=13, 48%) or usual care (n=14, 52%). Of these 27 patients, 11 (41%) in the intervention group (iCardia4HF) and 14 (52%) in the usual care group started their assigned care and were included in the full analysis. Patients' mean age was 56 (SD 8.3) years, 44% (11/25) were female, 92% (23/25) self-reported race as Black, 76% (19/25) had NYHA class II or III HF, and 60% (15/25) had HF with reduced left ventricular ejection fraction. Participant retention, completion of study visits, and adherence to using the mHealth apps and devices for daily self-monitoring were high (>80%). At 8 weeks, the mean group differences in changes in the SCHFI subscale scores favored the intervention over the control group: maintenance (Cohen d=0.19, 95% CI -0.65 to 1.02), symptom perception (Cohen d=0.33, 95% CI -0.51 to 1.17), and self-care management (Cohen d=0.25, 95% CI -0.55 to 1.04). The greatest improvements in terms of effect size were observed in self-efficacy (Cohen d=0.68) and health beliefs about medication adherence (Cohen d=0.63) and self-monitoring adherence (Cohen d=0.94). There were no adverse events due to the intervention.

iCardia4HF was found to be feasible, acceptable, and safe. A larger trial with a longer follow-up duration is warranted to examine its efficacy among patients with HF.

ClinicalTrials.gov NCT03642275; https://clinicaltrials.gov/study/NCT03642275.

Exercise and mindfulness-based interventions have growing evidence for managing fatigue and comorbid symptoms; however, packaging them in a cohesive digital way for patients undergoing cancer treatment has not been evaluated. We conducted a randomized controlled trial to assess the impact of a 12 week digital integrative medicine program, Integrative Medicine at Home (IM@Home), versus enhanced usual care on fatigue severity (primary outcome), comorbid symptoms and acute healthcare utilization (secondary outcomes), in 200 patients with solid tumors experiencing fatigue during treatment. Fatigue severity decreased more in IM@Home than in the control (1.99 vs. 1.51 points; p = 0.04). IM@Home participants also had reduced symptom distress (p = 0.003), anxiety (p = 0.03), and depression (p = 0.02). Acute healthcare utilization was lower with IM@Home, with fewer emergency department visits (rate ratio 0.49; p = 0.04), hospitalizations (4% vs. 12.9%; p = 0.03), and shorter hospital stays (4.25 vs. 10 days; p < 0.001). These promising findings should be confirmed in phase III clinical trials. "Study registered at clinicaltrials.gov (NCT05053230) on 09-20-2021".

Studies of the world health organization indicated that Diabetes is on the rise. The occurrence of diabetes is steadily increasing everywhere, most markedly in the world's middle and low-income countries. The aim of this study is to explore the consequence of war on the sugar level of diabetic mellitus patients.

A retrospective longitudinal study with a sample of 67 diabetic mellitus patients was used. As a result, longitudinal different models, which are generalized linear mixed effects and nonlinear mixed effect models were fitted on the continuous response variable, the Sugar Level of the diabetic patients.

The results depicted that Blood Sugar Level of the patients increases over time. Moreover, as age, weight, medication, total cholesterol, high density lipoprotein (HDL), creatinine and linear time effect increase, Blood Sugar Level increases significantly, whereas triglyceride and low density lipoprotein increase, Blood Sugar Level of the adult Diabetes mellitus patients decreases.

The war has significant effect on the poor control of blood glucose level of the adult diabetic patients in Tigray region, Ethiopia. Due to the war, siege or blockages, in return there were rare of medicine, the patients were not taking their medicines on time, and they did not get enough insulin as well.

To investigate the impact of blood pressure (BP) on rates of retinal nerve fiber layer (RNFL) thinning in glaucomatous eyes with focal ischemic (FI) vs. generalized cup enlargement (GE) optic disc phenotypes.

Prospective cohort study.

The study included 122 eyes from 101 patients diagnosed with primary open-angle glaucoma. Eyes were classified as FI (n = 31, 25%) or GE (n = 91, 75%) based on masked grading of stereophotographs at baseline.

Subjects underwent comprehensive ophthalmic examinations, including intraocular pressure (IOP) measurement and spectral-domain OCT scans, every 6 months for an overall mean follow-up of 4.2 years ± 1.5 years. Brachial artery BP was measured concurrently, and mean arterial pressure (MAP), systolic arterial pressure (SAP), and diastolic arterial pressure (DAP) were calculated. Rates of global RNFL thickness change over time were assessed using linear mixed models, evaluating the impact of BP parameters in each optic disc phenotype, adjusting for IOP and other confounders. Interaction terms were used to test for differences in the effects of BP and IOP between the FI and GE phenotypes.

Effect of MAP, SAP, and DAP on rates of RNFL loss over time in FI and GE optic disc phenotypes.

In the adjusted FI group models, each 10 mmHg decrease in MAP, SAP, and DAP was associated with -0.397 μm/year (P = 0.006), -0.211 μm/year (P = 0.029), and -0.471 μm/year (P = 0.005) faster RNFL thinning, respectively. In contrast, BP parameters were not significantly associated with RNFL loss in the GE group. In the multivariable model with interaction terms, the interaction between DAP and phenotype was statistically significant (P = 0.019), indicating the FI phenotype exhibited greater sensitivity to lower diastolic pressure compared to GE eyes. In contrast, interaction terms between IOP and optic disc phenotype were not significant in any of the models, suggesting a similar effect of IOP in both phenotypes.

Lower systemic BP levels were associated with faster RNFL thinning in the FI optic disc phenotype but not in the GE phenotype. These findings highlight the importance of considering both IOP and systemic BP when managing patients with the FI optic disc phenotype.

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Behavioural variant frontotemporal dementia (bvFTD) is a clinical syndrome caused primarily by either tau (bvFTD-tau) or transactive response DNA-binding protein of 43 kDa (TDP-43) (bvFTD-TDP) proteinopathies. We previously found that lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, the patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD are understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topological order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e. periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex and eulaminate-II isocortex) spanning the anterior cingulate, paracingulate, orbitofrontal and mid-frontal gyri in bvFTD-tau (n = 27), bvFTD-TDP (n = 47) and healthy controls (n = 32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biological variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for healthy controls, validating our measures within the cortical gradient framework. The SMI32-ir loss was relatively uniform along the cortical gradient in bvFTD-TDP, whereas SMI32-ir decreased progressively along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau versus bvFTD-TDP (P = 0.039). Using a ratio of SMI32-ir to model known long-range connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio in bvFTD-tau versus bvFTD-TDP (P = 0.019), suggesting that select long-projecting pathways might contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau versus bvFTD-TDP (P = 0.047), suggesting that pyramidal neurodegeneration might occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir was related to behavioural severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest that loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that worsens selectively along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration might preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients might be an important neuroanatomical framework for identifying which types of cells and pathways are involved differentially between proteinopathies.

During the drug development process, testing potency plays an important role in the quality assessment required for the manufacturing and marketing of biologics. Due to multiple operational and biological factors, higher variability is usually observed in bioassays compared with physicochemical methods. In this paper, we discuss different sources of bioassay variability and how this variability can be statistically estimated. In addition, we propose an algorithm to estimate the variability of reportable results associated with different numbers of runs and their corresponding OOS rates under a given specification. Numerical experiments are conducted on multiple assay formats to elucidate the empirical distribution of bioassay variability.